Delete train_custommade.py

train_custommade.py

@@ -1,35 +0,0 @@
-import json
-import torch.nn as nn
-import torch
-from model import MiniGPT
-from dataset import DataLoader,ChatDataset,SimpleTokenizr
-from tqdm import tqdm
-
-with open("./customchatbot-v1/data/merged_data.jsonl", "r", encoding="utf-8") as f:
-    texts = [json.loads(line)["text"] for line in f if line.strip()]
-
-tokenizer = SimpleTokenizr()
-tokenizer.train(texts)
-
-model = MiniGPT(vocab_size=100)
-
-criterion = nn.CrossEntropyLoss()
-optimizer = torch.optim.Adam(model.parameters(),lr=0.001)
-device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-model.to(device)
-
-dataset = ChatDataset("./customchatbot-v1/data/merged_data.jsonl", tokenizer)
-dataloader = DataLoader(dataset, batch_size=100, shuffle=True)
-
-def Train(epochs):
-    for epoch in range(epochs):
-        model.train()
-        loop = tqdm(enumerate(dataloader),total=len(dataloader),desc="Training")
-        tloss = 0
-        for i,l in loop:
-            optimizer.zero_grad()
-            outputs = model(i)
-            loss = criterion(outputs,l)
-            loss.backward()
-
-Train(epochs=1)